Job Location: Cupertino, CA
Summary
Posted: Oct 14, 2022
Role Number:200376256
The key to successful Machine Learning Teams is an efficient, robust, flexible and scalable architectural foundation. The Apple Special Projects Group on Autonomous Systems is looking for a talented, dedicated and result oriented software engineer to help build and improve our Machine Learning Systems. This fundamental and highly impactful work enables us to architect, train, evaluate and deploy state of the art machine learning models for Autonomous Systems. You will be part of a world class team with a highly diverse skillsets. From implementing CUDA kernels, optimizing cache coherency of complex algorithms, reducing memory footprints all the way to optimizing distributed training setups and implementing efficient large scale cloud compute schedules, ML Systems & Performance engineers are taking a holistic view at the whole stack to eliminate bottlenecks resulting in a lean and optimally efficient implementation.
Key Qualifications
- 3+ years of professional software development experience.
- Familiarity with modern Machine Learning frameworks like PyTorch.
- Familiarity with optimization techniques like Quantization, sparsity and/or pruning.
- Experience in architecting and implementing large-scale cloud pipelines., e.g using spark, kafka, kubeflow, postgres
- High proficiency in Python, C++ and/or CUDA.
- Passion for optimizations and efficient implementations.
- High software engineering standards: desire to write clean, well-tested and well-structured code.
- Track record of collaborations across teams, including requirement specifications and successful project delivery.
- Excellent communication and presentation skills.
- Curiosity to learn new things and push the boundary towards new approaches without fear of changing existing paradigms.
Description
• Improve ML Training efficiency to models train faster by scaling out and scaling up. • Develop strategies for training distributed models to accommodate model growth beyond state-of-the-art. • Design and implement a highly scalable inference pipelines for large scale evaluation. • Architect a data processing framework training data preparation and auto-labeling. • Collaborate with ML engineers to remove bottlenecks and improve turn-around times. • Build visualizations and dashboards to monitor cloud resource utilization.
Education & Experience
Additional Requirements
- This posting is not for a specific job opening and by submitting your resume you are expressing interest in being contacted about this type of role at Apple in the future.
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